• 제목/요약/키워드: Job matching

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Job Mismatch in Korean Regional labor Market: Matching Efficiency Analysis using Stochastic Production Frontier Approach (한국 지역노동시장에서의 일자리 미스매치에 관한 연구 - 확률변경생산함수를 이용한 결합 효율성 분석 -)

  • Yang, Jun Seok;Jeon, Yongil
    • Journal of the Economic Geographical Society of Korea
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    • 제15권4호
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    • pp.752-765
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    • 2012
  • We analyze the relation empirically between regional labor market characteristics and job matching efficiency with the adaption of stochastic frontier production function. Our empirical results suggest that, as both the ratio of 50 years-old-job seekers and the level of spatial density increase, job matching efficiencies also rise. In contrast, an increase in the ratio of firms which offer permanent contracts lowers job matching efficiencies. And the job matching efficiency is relatively higher in metropolitan areas. Finally, We find a negative relation between total industrial production and job matching efficiency, which implies that job seekers tend to accept uncongenial jobs in the recessions.

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Estimation of Aggregate Matching Function in Korea (한국의 구인·구직 매칭함수 추정)

  • Lee, Daechang
    • Journal of Labour Economics
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    • 제38권1호
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    • pp.1-30
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    • 2015
  • The aggregate matching function is estimated to explain dynamics among job seekers, vacancies and new hires in Korea. Due to measurement errors inherent in vacancies data, I introduce a latent variable for job openings and use the instrumental variables to correct its endogeneity. Matching efficiency is also estimated using some explanatory variables like job seekers' characteristics and public employment services. The result shows that Korea's matching function also exhibits a constant returns to scale.

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Job Preference Analysis and Job Matching System Development for the Middle Aged Class (중장년층 일자리 요구사항 분석 및 인력 고용 매칭 시스템 개발)

  • Kim, Seongchan;Jang, Jincheul;Kim, Seong Jung;Chin, Hyojin;Yi, Mun Yong
    • Journal of Intelligence and Information Systems
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    • 제22권4호
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    • pp.247-264
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    • 2016
  • With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

Job-Matching Function Analysis Using Social Network Analysis (사회연결망분석을 이용한 잡매칭함수 분석)

  • Cho, Jang-Sik;Park, Sung-Ik
    • Communications for Statistical Applications and Methods
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    • 제18권6호
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    • pp.675-685
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    • 2011
  • This paper proposes a job matching function that calculates the job matching probability of a job-seeker to an employer taking the working conditions of a job-seeker and an employer into account. In addition, this study analysis the degree of centrality that means interactions of a job-seeker and an employer utilizing social network analysis. The results are follows. First, a degree of centrality is found to be severely concentrated in certain job-seekers or certain employers; in addition, there are many job-seekers and employers who have no matching results. Second, according to decision tree analysis, characteristics of a job-seeker that influences the degree of centrality are gender, age and degree of education in order of importance. The characteristics of a employer that influences the degree of centrality are proposed salary, industry classification and firm size in order of importance.

A Design of Content-based Metric Learning Model for HR Matching (인재매칭을 위한 내용기반 척도학습모형의 설계)

  • Song, Hee Seok
    • Journal of Information Technology Applications and Management
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    • 제27권6호
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    • pp.141-151
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    • 2020
  • The job mismatch between job seekers and SMEs is becoming more and more intensifying with the serious difficulties in youth employment. In this study, a bi-directional content-based metric learning model is proposed to recommend suitable jobs for job seekers and suitable job seekers for SMEs, respectively. The proposed model not only enables bi-directional recommendation, but also enables HR matching without relearning for new job seekers and new job offers. As a result of the experiment, the proposed model showed superior performance in terms of precision, recall, and f1 than the existing collaborative filtering model named NCF+GMF. The proposed model is also confirmed that it is an evolutionary model that improves performance as training data increases.

On the Estimation of Regional Job-matching Functions of Korea (우리나라의 지역별 일자리결합함수의 추정)

  • Yang, Jun-Seok;Kim, Ho-Yeon
    • Journal of the Economic Geographical Society of Korea
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    • 제12권3호
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    • pp.248-259
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    • 2009
  • This paper analyzes the interactions among regional labor markets in Korea. Specifically, we focus on the job market externality between neighboring regions. To estimate the job matching functions, we construct panel data on unemployment, vacancies and hires for the period of January 2004 through December 2007 for 15 cities and provinces in Korea. We employ various spatial econometric techniques to avoid the problem of spatial autocorrelation which frequently arises when dealing with regional data. Main findings are as follows. First, estimation results are consistent with conventional job matching theory. That is, as the number of job searchers and vacancies increase, the number of hires also rises. And it is relatively easier for firms to hire workers than for job seekers to find jobs. Second, it is found that, other things equal, the possibility of job matching is higher in large metropolitan areas than rural areas. Finally, the findings show that the number of job searchers in neighboring areas is negatively correlated with the number of hires in the area. Likewise, the number of vacancies in neighboring areas is positively correlated with number of hires in the area. These provide clear evidence on the existence of regional spillover effects.

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A BERT-based Transfer Learning Model for Bidirectional HR Matching (양방향 인재매칭을 위한 BERT 기반의 전이학습 모델)

  • Oh, Sojin;Jang, Moonkyoung;Song, Hee Seok
    • Journal of Information Technology Applications and Management
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    • 제28권4호
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    • pp.33-43
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    • 2021
  • While youth unemployment has recorded the lowest level since the global COVID-19 pandemic, SMEs(small and medium sized enterprises) are still struggling to fill vacancies. It is difficult for SMEs to find good candidates as well as for job seekers to find appropriate job offers due to information mismatch. To overcome information mismatch, this study proposes the fine-turning model for bidirectional HR matching based on a pre-learning language model called BERT(Bidirectional Encoder Representations from Transformers). The proposed model is capable to recommend job openings suitable for the applicant, or applicants appropriate for the job through sufficient pre-learning of terms including technical jargons. The results of the experiment demonstrate the superior performance of our model in terms of precision, recall, and f1-score compared to the existing content-based metric learning model. This study provides insights for developing practical models for job recommendations and offers suggestions for future research.

Implementing a Company Assessment Support System on Job Seekers' Preferences : Using Fuzzy-Analytic Hierarchy Process and Career Maturity (구직자 선호요인 기반 기업평가 지원시스템 구현 : 퍼지 AHP와 진로성숙도 활용)

  • Ryou, Okhyun;Lee, Choongseok
    • Journal of Korean Society of Industrial and Systems Engineering
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    • 제38권2호
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    • pp.63-71
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    • 2015
  • This study is about implementing an job matching web service system based on the Job seeker's company assessment model proposed by the researchers. Basically, the Job seekers' company assessment model is based on the concept that each job seeker can evaluate the recruitment company candidates using job seekers's own major consideration factors. Using the implemented information system, each job seeker's main considerations in job searching process are evaluated and stored and compared to those of other job seekers' or groups' characterized by sex, job experience residential area and etc. by finding out and listing up the companies in the order of the preference of job seeker own or belonging groups, job seekers can be helped to find suitable companies which fit well to themselves.

A Study on Smart Job Matching Platform for Personal Assistant of the Disabled (장애인 활동보조인의 구인·구직을 위한 비대면 플랫폼에 관한 연구)

  • Kang, Seungae
    • Convergence Security Journal
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    • 제21권3호
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    • pp.75-80
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    • 2021
  • This study provided personnel and recruitment information related to job offer and job hunting, and proposed a non-face-to-face platform that can facilitate matching of one-time services as well as periodic services. The existing recruitment and job search method for personal assistant of the disabled is a one-way matching method in which a person in charge of the service providing centers assigns an activity assistant belonging to the institution when a consumer requests an personal assistant service, so the choice of job seekers is very weak. The job matching platform of the activity assistant for the disabled can be logged in separately by dividing users and separating them into the interface of the disabled or the disabled family members (job seekers) and activity assistants for the disabled (job seekers). Search for job offer and job seekers that meet their respective conditions, and real-time bidirectional decision-making through the chat function, and when the activity assistance service is completed, recruiters and job seekers can write service reviews and evaluations from their own point of view. The real-time interactive decision-making matching platform will also help minimize blind spots where it is difficult to provide services when short-term or one-time assistance is needed.

A Study on Improving Recruiting-Job Seeking Matching Service for Software Developers (소프트웨어인력 취업과 채용 매칭서비스 개선방안 연구)

  • Kim, Hyunsoo
    • Journal of Service Research and Studies
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    • 제3권1호
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    • pp.55-73
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    • 2013
  • The purpose of this research is to find a solution for matching service between recruiting and job seeking of software developers. An efficient matching service solution is essential for acquiring solid global competitiveness in software industry and IT academia. An in-depth analysis on deep-rooted problems on mismatching has been performed. Past and present policies on mismatching solutions have been reviewed based on desirable co-growth structure. A new matching solution has been derived and a triple-helix strategy has been suggested. A survey result for 14 domain experts and 85 employees of large and small software companies shows that the suggested matching solution is useful. The results of this research can be used for finding a better matching service solution and policies.

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